The Power to Resolve Cultural Transmission and Sibling Interaction Using Polygenic Scores

In the classical twin design, the assumption that the additive genetic (A) and shared environment (C) variance components are uncorrelated may not hold. If there is positive AC covariance, the C component is overestimated. While many processes can lead to AC covariance, in this study, we focus on two widely-studied mechanisms: Cultural transmission (e.g., genetic nurture), when the parents' genotypes contribute to the effective environment of the child, and sibling interaction, when the genotype of one sibling contributes to the effective environment of another. Several designs use polygenic scores of parents or siblings to detect AC covariance, but these models cannot unambiguously identify the source. A combined model has been proposed, but its power to identify both processes has not been well-studied yet. This study uses exact data simulation to investigate the power to disentangle these processes. Results demonstrated that we can detect AC covariance using either genotyped-sibling or genotyped-parent data, but we cannot resolve its source and thus risk making wrong inferences. These sources of AC covariance can be resolved using genotyped data of both siblings and parents. However, the power analyses show that large samples are required to do so. The sample sizes of published studies may be too small to unambiguously resolve the contributions of the two processes to AC covariance, especially if the effect of one is relatively small compared to the effect of the other. We implement these findings in an R package for genomic simulations, gnomesims, and emphasize the need for whole-family genotyping and modeling.